Algorithms

MIT researchers have developed a kind of creativity test for generative models to see how far they can go in visualizing objects in photos from various angles and in different colors. The tool shows how much the model's imagination depends on the variety of images it has seen.

Visualizing the world beyond the frame

Researchers test how far artificial intelligence models can go in dreaming up varied poses and colors of objects and animals in photos.

May 6, 2020

MIT researchers have proposed a technique for shrinking deep learning models that they say is simpler and produces more accurate results than state-of-the-art methods. It works by retraining the smaller, pruned model at its faster, initial learning rate.

A foolproof way to shrink deep learning models

Researchers unveil a pruning algorithm to make artificial intelligence applications run faster.

April 30, 2020

MIT researchers used machine learning to find entirely new algorithms for encoding exploration. Their machine-designed algorithms outperformed human-designed algorithms on the wide range of simulated tasks and environments shown here.

Automating the search for entirely new “curiosity” algorithms

Researchers show that computers can “write” algorithms that adapt to radically different environments better than algorithms designed by humans.

April 28, 2020

Lead author Joseph DelPreto controls a "Conduct-A-Bot" drone with his arm muscles.

Muscle signals can pilot a robot

CSAIL's Conduct-A-Bot system uses muscle signals to cue a drone’s movement, enabling more natural human-robot communication.

April 27, 2020

MIT researchers have developed a new automated AI system with improved computational efficiency and a much smaller carbon footprint. The researchers’ system trains one large neural network comprising many pretrained subnetworks of different sizes that can be tailored to diverse hardware platforms without retraining.

Reducing the carbon footprint of artificial intelligence

MIT system cuts the energy required for training and running neural networks.

April 23, 2020

In this lidar map, AI algorithms have identified roads (red). By pairing this map with OpenStreetMaps, users can plan routes around roads that are deemed impassable and can do so at the scale of an entire sortie, which here covers about 400 square miles.

With lidar and artificial intelligence, road status clears up after a disaster

Automated tools can help emergency managers make decisions, plan routes, and quantify road damage at city scales.

April 21, 2020

This research started as part of a project started in class 2.168 (Learning Machines), which was instructed by Professor George Barbastathis (pictured).

Model quantifies the impact of quarantine measures on Covid-19’s spread

A machine learning algorithm combines data on the disease's spread with a neural network, to help predict when infections will slow down in each country.

April 16, 2020

To reduce lag times and increase quality in video streaming, mobile gaming, and other web services, researchers at MIT’s Computer Science and Artificial Intelligence Laboratory have designed a congestion-control scheme for time-varying wireless links, such as cellular networks.

Reducing delays in wireless networks

Congestion control system could help streaming video, mobile games, and other applications run more smoothly.

April 9, 2020

A simulation system invented at MIT to train driverless cars creates a photorealistic world with infinite steering possibilities, helping the cars learn to navigate a host of worse-case scenarios before cruising down real streets.

System trains driverless cars in simulation before they hit the road

Using a photorealistic simulation engine, vehicles learn to drive in the real world and recover from near-crash scenarios.

March 23, 2020

An algorithm designed to predict the biological effects of 800 “inactive” pill ingredients uncovered thousands of previously undocumented effects. In this visualization of the researchers’ results, inactive ingredients are shown in blue and their protein targets, in red. The number of predicted, and yet-to-be-verified, interactions (gray edges) outnumber those documented so far (in black).

“Inactive” pill ingredients could raise the dose of your medication

With help from artificial intelligence, researchers identify hidden power of vitamin A and ordinary chewing gum glaze.

March 17, 2020

“Doing machine learning the right way”

Professor Aleksander Madry strives to build machine-learning models that are more reliable, understandable, and robust.

March 7, 2020

Roboticists are developing automated robots that can learn new tasks solely by observing humans. At home, you might someday show a domestic robot how to do routine chores.

Showing robots how to do your chores

By observing humans, robots learn to perform complex tasks, such as setting a table.

March 5, 2020

In a new metadata-protecting scheme, users send encrypted messages to multiple chains of servers, with each chain mathematically guaranteed to have at least one hacker-free server. Each server decrypts and shuffles the messages in random order, before shooting them to the next server in line.

Protecting sensitive metadata so it can’t be used for surveillance

System ensures hackers eavesdropping on large networks can’t find out who’s communicating and when they’re doing so.

February 26, 2020

A crash course in deep learning organized and taught by grad students Alexander Amini (right) and Ava Soleimany reaches more than 350 MIT students each year; more than a million other people have watched their lectures online over the past three years.

Bringing deep learning to life

MIT duo uses music, videos, and real-world examples to teach students the foundations of artificial intelligence.

February 24, 2020

MIT researchers used a machine-learning algorithm to identify a drug called halicin that kills many strains of bacteria. Halicin (top row) prevented the development of antibiotic resistance in E. coli, while ciprofloxacin (bottom row) did not.

Artificial intelligence yields new antibiotic

A deep-learning model identifies a powerful new drug that can kill many species of antibiotic-resistant bacteria.

February 20, 2020

MIT News | Massachusetts Institute of Technology - On Campus and Around the world

Browse By

Topics

Departments

Centers, Labs, & Programs

Schools

Topic